US20120183222A1 - Computing device and method for automatically typesetting patent images - Google Patents
Computing device and method for automatically typesetting patent images Download PDFInfo
- Publication number
- US20120183222A1 US20120183222A1 US13/337,119 US201113337119A US2012183222A1 US 20120183222 A1 US20120183222 A1 US 20120183222A1 US 201113337119 A US201113337119 A US 201113337119A US 2012183222 A1 US2012183222 A1 US 2012183222A1
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- United States
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/103—Formatting, i.e. changing of presentation of documents
- G06F40/106—Display of layout of documents; Previewing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/14—Image acquisition
- G06V30/1444—Selective acquisition, locating or processing of specific regions, e.g. highlighted text, fiducial marks or predetermined fields
- G06V30/1448—Selective acquisition, locating or processing of specific regions, e.g. highlighted text, fiducial marks or predetermined fields based on markings or identifiers characterising the document or the area
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/14—Image acquisition
- G06V30/146—Aligning or centring of the image pick-up or image-field
- G06V30/1463—Orientation detection or correction, e.g. rotation of multiples of 90 degrees
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
Definitions
- Embodiments of the present disclosure generally relate to typesetting technology, and more particularly to a computing device and a method for automatically typesetting patent images.
- patent images in a patent document are displayed according to a proportion of height and width of each patent image. If the width of one patent image is greater than the height of the patent image, the patent image may be counter-clockwise rotated by ninety degrees. It is inconvenient for users to read the patent document because they have to rotate the patent image clockwise first.
- FIG. 1 is a block diagram of one embodiment of a computing device including a typesetting unit for automatically typesetting patent images.
- FIG. 2 is a flowchart of one embodiment of a method for automatically typesetting patent images.
- module refers to logic embodied in hardware or firmware, or to a collection of software instructions, written in a programming language, such as, Java, C, or assembly.
- One or more software instructions in the modules may be embedded in firmware, such as in an EPROM.
- the modules described herein may be implemented as either software and/or hardware modules and may be stored in any type of non-transitory computer-readable medium or other storage device.
- Some non-limiting examples of non-transitory computer-readable media include CDs, DVDs, BLU-RAY, flash memory, and hard disk drives.
- FIG. 1 is a block diagram of one embodiment of a computing device 1 including a typesetting unit 10 for automatically typesetting patent images.
- the computing device 1 further includes a storage unit 20 and a processor 30 .
- the computing device 1 electrically connects to a display device 2 .
- the storage unit 20 is operable to store patent documents (e.g., patent publications, and issued patents).
- Each of the patent documents includes a description part (e.g., the detailed description) and an image part.
- the image part includes one or more images of an invention of the patent document (“patent images”).
- the patent documents may be in various formats such as PDF or text.
- the typesetting unit 10 may include one or more function modules (detailed description given below).
- the one or more function modules may comprise computerized code in the form of one or more programs that are stored in the storage unit 20 , and executed by the processor 30 to provide the functions of the typesetting unit 10 described later.
- the storage unit 20 may be a cache or a memory, such as an EPROM or a flash memory.
- the typesetting unit 10 includes a first reading module 100 , an extracting module 200 , a second reading module 300 , a distinguishing module 400 , a comparison module 500 , and a processing module 600 .
- the first reading module 100 is operable to read a description part of a patent document. It is understood that the description part includes text of the detailed description of the patent document. The description part may also include description of the prior art, claims, and abstract depending on the embodiment.
- the extracting module 200 is operable to extract a brief introduction of each patent image from the description part of the patent document, and record a keyword of the brief introduction of each patent image.
- the brief introductions of patent images can be extracted according to a regular expression.
- the brief introductions of patent images in US patents may be: “ FIG. 1A shows a side view of a single unit auto rack rail road car”.
- the extracting module 200 extracts the regular expression which includes a label of the patent image, where the label of the patent image includes a fixed phrase “FIG” and a number (such as “ 1 A”), and records the fixed phrase “FIG” or the label of the patent image (such as “FIG. 1 A”) as the keyword of the brief introduction of the patent image.
- the second reading module 300 is further operable to read all images in an image part of the patent document. All of the images may include reading just one image if the patent document only has one image or reading multiple images if the patent document includes multiple images.
- the distinguishing module 400 is operable to distinguish an image label for each patent image from the image part.
- the image labels such as “FIG. 1 A” and “FIG. 1 B”, are at the bottom of the patent images.
- the distinguishing module 400 distinguishes the image labels by Optical Character Recognition (OCR) technology. If one patent image is not displayed in the right direction (i.e., the wrong direction), the distinguishing module 400 records that the image label is NULL.
- OCR Optical Character Recognition
- the wrong direction of the one patent image may be defined if width of one patent image is greater than height of the patent image, thus the user may desire the patent image to be rotated counter-clockwise by ninety degrees in the patent document.
- the comparison module 500 is operable to compare the image label of each patent image with the keyword of the brief introduction of the patent image, and determine whether the image label contains the keyword.
- the processing module 600 is operable to rotate the patent image by ninety degrees clockwise when the image label of the patent image does not contain the keyword, and then output the rotated image on the display device 2 .
- the image label of one patent image is NULL
- the keyword is “FIG”, so the image label does not contain the keyword
- the processing module 600 rotates the patent image by ninety degrees clockwise and then outputs the rotated image on the display device 2 .
- the processing module 600 is further operable to output the patent image on the display device 2 when the image label of the patent image contains the keyword of the brief introduction of the patent image.
- the image label of one patent image is “FIG. 1 A”
- the keyword of the brief introduction of the patent image is “FIG”
- the processing module 600 outputs the patent image on the display device 2 .
- FIG. 2 is a flowchart of one embodiment of a method for automatically typesetting patent images. Depending on the embodiment, additional blocks may be added, others removed, and the ordering of the blocks may be changed.
- the first reading module 100 reads a description part of a patent document.
- the extracting module 200 extracts a brief introduction of each patent image from the description part of the patent document, and record a keyword of the brief introduction of each patent image.
- the second reading module 300 reads all images in an image part of the patent document.
- the distinguishing module 400 distinguishes an image label for each patent image from the image part. If one patent image is not displayed in the right dimension, the distinguishing module 400 records that the image label is NULL.
- the comparison module 500 compares the image label of each patent image with the keyword of the brief introduction of the patent image, and determine whether the image label contains the keyword. If the image label of the patent image does not contain the keyword, block S 20 is implemented. Otherwise, if the image label of the patent image contains the keyword, block S 22 is implemented.
- the processing module 600 rotates the patent image by ninety degrees clockwise, and then outputs the rotated image on the display device 2 .
- the image label of one patent image is NULL, and the keyword is “FIG”, so the image label does not comprise the keyword, and the processing module 600 rotates the patent image by ninety degrees clockwise and then outputs the rotated image on the display device 2 .
- the processing module 600 outputs the patent image on the display device 2 .
- the image label of one patent image is “FIG. 1 A”
- the keyword of the brief introduction of the patent image is “FIG”
- the image label contains the keyword
- the processing module 600 outputs the patent image on the display device 2 .
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- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Processing Or Creating Images (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Editing Of Facsimile Originals (AREA)
Abstract
Description
- 1. Technical Field
- Embodiments of the present disclosure generally relate to typesetting technology, and more particularly to a computing device and a method for automatically typesetting patent images.
- 2. Description of Related Art
- Usually, patent images in a patent document are displayed according to a proportion of height and width of each patent image. If the width of one patent image is greater than the height of the patent image, the patent image may be counter-clockwise rotated by ninety degrees. It is inconvenient for users to read the patent document because they have to rotate the patent image clockwise first.
-
FIG. 1 is a block diagram of one embodiment of a computing device including a typesetting unit for automatically typesetting patent images. -
FIG. 2 is a flowchart of one embodiment of a method for automatically typesetting patent images. - The application is illustrated by way of examples and not by way of limitation in the figures of the accompanying drawings in which like references indicate similar elements. It should be noted that references to “an” or “one” embodiment in this disclosure are not necessarily to the same embodiment, and such references mean at least one.
- In general, the word “module”, as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions, written in a programming language, such as, Java, C, or assembly. One or more software instructions in the modules may be embedded in firmware, such as in an EPROM. The modules described herein may be implemented as either software and/or hardware modules and may be stored in any type of non-transitory computer-readable medium or other storage device. Some non-limiting examples of non-transitory computer-readable media include CDs, DVDs, BLU-RAY, flash memory, and hard disk drives.
-
FIG. 1 is a block diagram of one embodiment of a computing device 1 including atypesetting unit 10 for automatically typesetting patent images. The computing device 1 further includes astorage unit 20 and aprocessor 30. The computing device 1 electrically connects to adisplay device 2. - The
storage unit 20 is operable to store patent documents (e.g., patent publications, and issued patents). Each of the patent documents includes a description part (e.g., the detailed description) and an image part. The image part includes one or more images of an invention of the patent document (“patent images”). The patent documents may be in various formats such as PDF or text. - In one embodiment, the typesetting
unit 10 may include one or more function modules (detailed description given below). The one or more function modules may comprise computerized code in the form of one or more programs that are stored in thestorage unit 20, and executed by theprocessor 30 to provide the functions of thetypesetting unit 10 described later. Thestorage unit 20 may be a cache or a memory, such as an EPROM or a flash memory. - In one embodiment, the
typesetting unit 10 includes afirst reading module 100, anextracting module 200, asecond reading module 300, adistinguishing module 400, acomparison module 500, and a processing module 600. - The
first reading module 100 is operable to read a description part of a patent document. It is understood that the description part includes text of the detailed description of the patent document. The description part may also include description of the prior art, claims, and abstract depending on the embodiment. - The extracting
module 200 is operable to extract a brief introduction of each patent image from the description part of the patent document, and record a keyword of the brief introduction of each patent image. In some embodiments, the brief introductions of patent images can be extracted according to a regular expression. For example, the brief introductions of patent images in US patents may be: “FIG. 1A shows a side view of a single unit auto rack rail road car”. The extractingmodule 200 extracts the regular expression which includes a label of the patent image, where the label of the patent image includes a fixed phrase “FIG” and a number (such as “1A”), and records the fixed phrase “FIG” or the label of the patent image (such as “FIG. 1A”) as the keyword of the brief introduction of the patent image. - The
second reading module 300 is further operable to read all images in an image part of the patent document. All of the images may include reading just one image if the patent document only has one image or reading multiple images if the patent document includes multiple images. - The
distinguishing module 400 is operable to distinguish an image label for each patent image from the image part. The image labels, such as “FIG. 1A” and “FIG. 1B”, are at the bottom of the patent images. In one embodiment, thedistinguishing module 400 distinguishes the image labels by Optical Character Recognition (OCR) technology. If one patent image is not displayed in the right direction (i.e., the wrong direction), thedistinguishing module 400 records that the image label is NULL. The wrong direction of the one patent image may be defined if width of one patent image is greater than height of the patent image, thus the user may desire the patent image to be rotated counter-clockwise by ninety degrees in the patent document. - The
comparison module 500 is operable to compare the image label of each patent image with the keyword of the brief introduction of the patent image, and determine whether the image label contains the keyword. - The processing module 600 is operable to rotate the patent image by ninety degrees clockwise when the image label of the patent image does not contain the keyword, and then output the rotated image on the
display device 2. For example, the image label of one patent image is NULL, and the keyword is “FIG”, so the image label does not contain the keyword, and the processing module 600 rotates the patent image by ninety degrees clockwise and then outputs the rotated image on thedisplay device 2. - The processing module 600 is further operable to output the patent image on the
display device 2 when the image label of the patent image contains the keyword of the brief introduction of the patent image. For example, the image label of one patent image is “FIG. 1A”, and the keyword of the brief introduction of the patent image is “FIG”, so the image label contains the keyword, and the processing module 600 outputs the patent image on thedisplay device 2. -
FIG. 2 is a flowchart of one embodiment of a method for automatically typesetting patent images. Depending on the embodiment, additional blocks may be added, others removed, and the ordering of the blocks may be changed. - In block S10, the
first reading module 100 reads a description part of a patent document. - In block S12, the extracting
module 200 extracts a brief introduction of each patent image from the description part of the patent document, and record a keyword of the brief introduction of each patent image. - In block 514, the
second reading module 300 reads all images in an image part of the patent document. - In block S16, the
distinguishing module 400 distinguishes an image label for each patent image from the image part. If one patent image is not displayed in the right dimension, thedistinguishing module 400 records that the image label is NULL. - In block 518, the
comparison module 500 compares the image label of each patent image with the keyword of the brief introduction of the patent image, and determine whether the image label contains the keyword. If the image label of the patent image does not contain the keyword, block S20 is implemented. Otherwise, if the image label of the patent image contains the keyword, block S22 is implemented. - In block S20, the processing module 600 rotates the patent image by ninety degrees clockwise, and then outputs the rotated image on the
display device 2. For example, the image label of one patent image is NULL, and the keyword is “FIG”, so the image label does not comprise the keyword, and the processing module 600 rotates the patent image by ninety degrees clockwise and then outputs the rotated image on thedisplay device 2. - In block S22, the processing module 600 outputs the patent image on the
display device 2. For example, the image label of one patent image is “FIG. 1A”, and the keyword of the brief introduction of the patent image is “FIG”, so the image label contains the keyword, and the processing module 600 outputs the patent image on thedisplay device 2. - Although certain inventive embodiments of the present disclosure have been specifically described, the present disclosure is not to be construed as being limited thereto. Various changes or modifications may be made to the present disclosure beyond departing from the scope and spirit of the present disclosure.
Claims (9)
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201110007622.3 | 2011-01-14 | ||
CN2011100076223A CN102591852A (en) | 2011-01-14 | 2011-01-14 | Automatic typesetting method and automatic typesetting system for patent images |
CN201110007622 | 2011-01-14 |
Publications (2)
Publication Number | Publication Date |
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US20120183222A1 true US20120183222A1 (en) | 2012-07-19 |
US8761547B2 US8761547B2 (en) | 2014-06-24 |
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ID=46480521
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Application Number | Title | Priority Date | Filing Date |
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US13/337,119 Expired - Fee Related US8761547B2 (en) | 2011-01-14 | 2011-12-25 | Computing device and method for automatically typesetting patent images |
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US (1) | US8761547B2 (en) |
CN (1) | CN102591852A (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2018174603A1 (en) * | 2017-03-22 | 2018-09-27 | (주)광개토연구소 | Method and device for displaying explanation of reference numeral in patent drawing image using artificial intelligence technology based machine learning |
WO2024158398A1 (en) * | 2023-01-26 | 2024-08-02 | Alex Edson | System and method for creating patent drawings using generative artificial inteligence (ai) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103677504A (en) * | 2012-09-19 | 2014-03-26 | 鸿富锦精密工业(深圳)有限公司 | File reader and file information display method |
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2011
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US5754840A (en) * | 1996-01-23 | 1998-05-19 | Smartpatents, Inc. | System, method, and computer program product for developing and maintaining documents which includes analyzing a patent application with regards to the specification and claims |
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WO2018174603A1 (en) * | 2017-03-22 | 2018-09-27 | (주)광개토연구소 | Method and device for displaying explanation of reference numeral in patent drawing image using artificial intelligence technology based machine learning |
US11080910B2 (en) | 2017-03-22 | 2021-08-03 | Kwanggetoco., Ltd. | Method and device for displaying explanation of reference numeral in patent drawing image using artificial intelligence technology based machine learning |
WO2024158398A1 (en) * | 2023-01-26 | 2024-08-02 | Alex Edson | System and method for creating patent drawings using generative artificial inteligence (ai) |
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CN102591852A (en) | 2012-07-18 |
US8761547B2 (en) | 2014-06-24 |
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